(a) Field of the Invention
The present invention relates to the field of automated, computer-aided asset allocation and asset monitoring apparatus in connection with automated alarm, monitoring or control systems. Data from locally arranged, protected databases can be transferred via a network to the asset allocation and asset monitoring apparatus and can be evaluated and in which electronic control signals and/or control data can be transmitted to at least one authorized receiver station. In particular, the invention relates to an asset allocation and asset monitoring apparatus in connection with automated alarm, monitoring or control systems.
(b) Brief Description of the Related Art
For the last 30 to 40 years, the technological world, particularly the opportunities for technical implementation of automated apparatuses for control and monitoring of complex systems, has changed fundamentally. Contributions to this have been made by the appearance of new and fast data systems together with memory units with, until then, unimaginable storage capacity. In addition, the sensor technology has become cheaper to the extent that measurement data can be collected and are collected in vast volumes and at marginal cost in almost all technical fields. This volume of data allows the design of new and, on the basis of the available data, more accurate monitoring and control systems. The technical implementation of the monitoring and control systems may be based both on statistical or stochastic modules and on extrapolation modules, particularly realtime extrapolation modules. Frequently, however, these measurement data which are required by the monitoring and control systems are sensitive data which are provided only under protection and/or under access control and frequently for a fee. These sensitive data may be subject both to copyright and to know-how protection. In many cases for control and monitoring, however, not all but rather only the smallest proportion of the information covered by the measurement data is required. Access to all the measurement data required may then be unattractive for the system or make little technical sense for a wide variety of reasons, for example because it is too expensive or because the complex evaluation is excessive or too time-consuming. In realtime systems, this may mean that there is no way of producing automated implementation from a technical point of view, particularly in the case of simpler systems.
Such monitoring and control systems may, at least in part, be coupled to the parameters of the international financial and economic markets or at least be correlated in some way on the basis of them. The international financial and economic markets, particularly with regard to the nonlinearity of the stock-market data, are of such complexity today that most technical implementations of monitoring and control systems which depend on the trend of the market or stock-market parameters experience technical failure in the reliable generation of signal and control data. However, the great boom in the stock markets in recent years has also been accompanied by a rise in the need for the most efficient and up-to-date monitoring and control systems possible for automation. These also include fully automated security portfolio management systems, which allow rapid response to present or expected price fluctuations in the securities. This applies particularly to small and medium-sized investors, since small and medium-sized investors usually have too small a portfolio to be able to set up meaningful and widely supported risk management. However, they frequently lack the know-how required for risk management, the necessary market analysis means and/or market knowledge and also the necessary access to sensitive and protected data. For the large, financially strong investors, the systems available in the background art exhibit the drawbacks that they can barely be reliably automated from a technical point of view, despite access to the relevant data, on account of the vast volume of data and cannot comprehensively take account of the available data when generating the control signals.
The background art contains various technical implementations of automated or semi-automated systems for managing security portfolios. By way of example, this involves evaluating stock-market data using algorithms in order to make statements about future price fluctuations. Examples of such algorithms can be found, inter alia, in “The Point And Figure Method, Victor deVilliers, Windsor Books 1933” or “Das grosse Buch der Technischen Indikatoren, T. Müller and H. Nietzer, Fachverlag für Wirtschaftsinformationen 1993” etc. On account of the highly nonlinear, chaotic behavior of stock-market prices, it is not possible to predict price fluctuations for longer periods even with the most modern prediction algorithms, however. This is another reason why it is extremely important for the investor to be able to react quickly to current or forecast price fluctuations. The background art exhibits various systems which allow a user to manage his portfolio by indicating price fluctuations for securities in his portfolio to him. Examples of these can be found in the U.S. Pat. No. 6,064,985 entitled “Automated portfolio management system with internet datafeed” and U.S. Pat. No. 6,144,947 entitled “System for automatically determining net capital deductions for securities held, and process for implementing same”, for example. In all solutions from the background art, the portfolio management systems need to have access to communication links such as the Internet, the PSTN (Public Switched Telephone Network) etc., which are not only used to access the stock-market data servers but can also be used to charge for the services obtained if necessary. The sometimes sensitive and protected data cannot be protected in this case but rather are charged to the user comprehensively.
The automated technical implementations of signal and control apparatuses may also relate to the management of catastrophe bonds or cat bonds. Cat bonds are a relatively new invention and have come about as a result of the failure of conventional intervention systems in the event of large-scale catastrophes. The globalization of the markets, the change of climate with numerous occurrences of catastrophes with a cross-regional effect (tsunamis, hurricanes, typhoons, earthquakes etc.) and the occurrence of a new dimension of terror and wars (e.g. attack on the World Trade Center, Iraq war, bath crisis, hurricanes on the west coast of America (New Orleans), tsunami in Asia) have produced a new dimension of catastrophes which has created the need for new technical options for implementing more efficient automated alarm, monitoring and/or intervention systems or apparatuses in order to be able to effectively intercept such events or their effect. On the one hand, malfunctions need to be prevented or need to be able to be detected and corrected in good time when they occur, and on the other hand it is also intended that such systems will be used to prevent the catastrophes from resulting in destabilization of the economy and/or stock markets or even world markets. In this case, with such intervention apparatuses, not only the type of intervention means (e.g. catastrophe resources, malfunction means etc.) can play a part but also the way in which the monitoring parameters measured by the pickup apparatuses and detection apparatuses are processed and are technically implemented for the purpose of controlling activation units for the intervention means or alarm means. However, it is precisely the technical implementation which causes problems which are very difficult to overcome today. One of the fundamental technical problems is particularly the stability of the systems, whether automated or semi-automated. In addition, the vast volume of data available today at any time from a wide variety of pickup apparatuses and detection apparatuses (e.g. wind speed sensors, satellite pictures, water level sensors, water and wind temperature sensors etc. etc.) makes monitoring through pure human action and perception virtually impossible. The technical implementation of such apparatuses should therefore, if possible, interact both with the pickup apparatuses and with the intervention means in fully automated fashion and in real time.
As far as their technical requirements and hence also their technical implementation are concerned, automated intervention systems differ greatly according to field, since their constraints differ very greatly from field of application to field of application. Thus, large-scale catastrophes, catastrophe damage or industrial accidents (such as the reactor fire in Chernobyl) obey completely different laws than malfunctions in the automotive industry or building sector, for example. The mathematical laws and corresponding methods are known abundantly in the background art. The technical implementation of appropriate signal and control apparatuses eludes the known background art almost entirely even in this field. When coping with malfunctions, caused by single, larger-scale catastrophes such as natural catastrophes, war or terror, coupled or uncoupled intervention systems are known in different variations in the background art. Thus, by way of example, local monitoring sensors and monitoring units connected to a central monitoring apparatus are known which are used for early warning identification and alerting. It is likewise known practice to transmit location-dependent electrical signals from these monitoring apparatuses periodically or upon request for the purpose of automated alarm triggering. Automated intervention monitoring apparatuses and appropriate methods, particularly cash-sum-value-based intervention monitoring apparatuses, as are required for automated insurance systems or damage cover systems, for example, may make up part of the technical implementation of such intervention apparatuses. The operational apparatuses associated with the intervention apparatus can ensure the operation of the intervention apparatus by means of periodic transfer or transfers of assignable, protected units (particularly cash-sum-value-based parameters) upon request, for example. The transfer can be made a plurality of times or once. For certain systems, reference is also made in this case to the operational apparatuses and/or operators being insured. Cash-value-based transfers can also be referred to as remuneration for the transfer (e.g. “cession”) of responsibility, e.g. in the form of a premium, in such systems independently of the technical implementation of the apparatus. The “policies” are frequently ascertained using complex mathematical insurance methods. In principle, the technical implementation of the present invention does not relate or relates only partially to cash-value-based elements, of such automated intervention systems, but rather quite generally to asset allocation and asset monitoring apparatuses with automated signal and control apparatuses.
In the background art, the technical implementations of intervention apparatuses usually have far too long a reaction time to be able to react meaningfully to catastrophes of larger proportions. In addition, the ever further reaching consequences result in instabilities which are almost impossible to handle with the ordinary systems. The effect of this is that mechanization can be ruled out to date. However, even unautomated systems are affected by these instabilities and have already resulted in several collapses in the relevant intervention systems. Semi-automated intervention apparatuses with cash-value-based modules having an, if possible, uncorrelated partial risk protection module with an interface to loan markets, what are known as insurance linked securities (ILS), have been known since the mid-1990s and today exhibit capitalization of between 8 and 10 billion US dollars, which documents the great success of these systems. In this case too, the technical implementations of “insurance linked securities”-based modules in the background art differ greatly from one another. The main representatives of the ILS systems are based on what are known as catastrophe bonds or cat bonds. The growing acceptance among large investors shows the worldwide significance of cat bonds. For insurance systems, reinsurance systems and an ever increasing number of industrial apparatuses, cat bonds can effectively be used to produce perennial protection against natural catastrophes etc. without the usual credit risk. Cat bond systems provide investors with attractive returns and the option of reducing a portfolio risk, since cat bonds in name have no correlation in their behavior to all other securities or financial market instruments. Cat bonds are securities or investments having the same function, whose performance rests upon the index of risks on the basis of natural catastrophes. Industrial apparatuses and systems from international firms to local insurance companies have used cat bonds to shove up or reduce their risks. In 2006 alone, the issue of such bonds doubled to over $4.9 billion and the intensity of the growth has continued uninterrupted in the first half of 2007. The growth has additionally been furthered by an increasing demand for cat bonds on the loan market. More and more investors are regarding cat bonds as a diversifying asset class or investment class with an excellent yield upon maturity. While the primary cat bond market continues to grow, the secondary cat bond market is becoming increasingly liquid. 2006 was a record year for the secondary market, in which just the exposure for natural catastrophes exceeded a multi-billion sum.
Despite all of the above describes improvements in the field of automated asset allocation and asset monitoring apparatuses, still further improvements of such apparatuses and methods are desired. For example, reliable automated control signals for portfolio management on the basis of appropriate cat bond indexes have the advantage that the cat bond market can become even more attractive to investors. However, such systems which could meet the demands for security and reliability are not known to date.